This work addresses the task of risk evaluation in traffic scenarios with limited observability due to restricted sensorial coverage. Here, we concentrate on intersection scenarios that are difficult to access visually. To identify the area of sight, we employ ray casting on a local dynamic map providing geometrical information and road infrastructure. Based on the area with reduced visibility, we first model scene entities that pose a potential risk without being visually perceivable yet. Then, we predict a worst-case trajectory in the survival analysis for collision risk estimation. Resulting risk indicators are utilized to evaluate the driver's current behavior, to warn the driver in critical situations, to give suggestions on how to act safely or to plan safe trajectories. We validate our approach by applying the resulting intersection warning system on real world scenarios. The proposed system's behavior reveals to mimic the general behavior of a correctly acting human driver.

翻译：本工作针对由于传感器覆盖受限导致可观测性不足的交通场景中的风险评估任务展开研究。我们重点关注视觉难以获取的交叉口场景。为确定可视区域，我们在提供几何信息与道路基础设施的局部动态地图上采用光线投射技术。基于视野受限区域，我们首先对当前尚不可见但存在潜在风险的场景实体进行建模。随后，在生存分析中预测最坏情况轨迹以进行碰撞风险评估。所得风险指标被用于评估驾驶员当前行为、在危急情况下向驾驶员发出警告、提供安全操作建议或规划安全轨迹。我们通过将所提出的交叉口预警系统应用于真实场景来验证该方法。系统行为表明其能够模拟人类驾驶员在正确操作时的普遍行为特征。